The implementation of Advanced Measurement Infrastructure – AMIs, in the installation of each customer of the electricity utility helps operators of the electricity distribution network to achieve optimization of network utilization, improve availability and reduce costs.
By 2020, Colombia has made considerable progress in formulating and approving the policies and creating the legal frameworks necessary to implement advanced metering infrastructure. In this formulation process, many interesting findings have emerged in :
- the benefits identified are several and apply to both users, distribution network operators (OR) marketers, and almost anyone who wants to know the characteristics of energy consumption in a sector, region or in any geographic region.
- For the benefits obtained, it is very convenient to install this infrastructure on each user’s meters, without generating cost to end users.
- The information manager would have the possibility of knowing in detail the consumption behavior of all users under its influence. For this reason, it must establish special security conditions for access to this information.
In this article we want to focus the analysis on the opportunities provided by installing each advanced power meter to the Network Operator (OR),
Different ways to achieve optimization in the operation of the power grid with the implementation of AMI to THE OR.
There are many benefits for the network operator. Most of them are based on the collection, integration, analysis and simulation of information about network behavior and demand forecasting and network operation.
- the reduction of losses. By being able to simulate and understand the distribution of energy throughout the substructure, it is possible to perform an energy balance by infrastructure and thus identify in which elements the losses occur.
- Capacity utilization analysis by system also allows to identify with greater accuracy the networks at maximum capacity and generate power quality problems at the top of the system. Through this same study, it is very possible to identify efficient investments to improve capacity problems. In this way, investments that would otherwise have to be made can be postponed.
- Reduced operation and maintenance costs. Maintenance can be performed only when the equipment or system is in a condition that requires maintenance. Even with the appropriate artificial intelligence models, it is possible to foresee with high certainty when equipment will fail and achieve maintenance optimization.
- Implement an efficiency control module, which corresponds to the measurement of key indicators or KPIs: Comparing between actual and expected data, as well as ensuring that it is within tolerance ranges with adequate statistical control. In general, efficiency refers to the ratio between inputs and outputs. o Efficiency can also be given by loss rates, better on-line monitoring and very close knowledge of the network operation. Many times the operating conditions of a system vary greatly from design to reality. With the right information it is very possible to monitor on-line the performance of the network, trigger alarms, and improve power quality, increase reliability and stabilize operating conditions to standard.
- Predictive maintenance or failure anticipation. Based on the use of predictive monitoring tools, the condition of assets is continuously monitored to prevent unexpected equipment failure. It seems impossible, but with the collection of appropriate data it is possible to identify indications of potential failures from the analysis of previous failures.
- A reduction in the unavailability time associated with the repair, by making it in advance conditions and being able to have planned materials, inputs,qualified human resources, spare parts, among others.
- Asset health. Based on the type of asset, the general operating condition of each system is rated, using as input data a specialized sensoric, generally linked to the manufacturer’s specifications and technical analysis of processes. Using an internationally recognized methodology developed by Toronto Hydro, it serves as a support for the definition of a maintenance strategy based on asset risk.
- Risk valuation. It consists of associating the consequences of equipment failure, valued in monetary terms, to the assets, generally in terms of the money generated by the energy it carries. In this way, it is possible to consider the risk per asset by simply multiplying the probability of failure by its consequences. In other words, the probability of failure of each of the components of the system can be valued, which added to the valuation of the impact or cost of failure.
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In general, it can be said that the realization of optimization benefits is achieved with:
Health Index Monitoring
o Based on the typology of available assets and data.
o Online and historical Operation, Inspection and Maintenance data processing.
o Default models, configurable and tailor-made
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Matriz de Riesgos
o Definition of failure modes.
o Criticality analysis based on consequences and probability of failure.
o Integration of Historical Maintenance Data
